A detailed guide outlining ten crucial questions to consider before initiating a data science project, covering everything from business requirements and mission statements to stakeholder management a
nd evaluation methods. The article provides practical insights and real-world examples to help data scientists plan and execute successful projects.
Reasons to Read -- Learn:
how to systematically plan and structure data science projects using a comprehensive ten-question framework that helps avoid common pitfalls and ensures project success.
practical approaches for securing stakeholder buy-in and managing project risks, based on real-world experiences and concrete examples from actual data science projects.
effective methods for evaluating project outcomes and selecting appropriate technical approaches, including specific techniques for data cleaning, analysis, and result validation.
publisher: @adeniranstephen7
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